code: def get_single_output_feature_tensors(
      output_feature_dict: Dict[str, torch.Tensor], feature_name: str
  ) -> Dict[str, torch.Tensor]:
      """Returns a map of tensors related to the given feature_name."""
      single_output_feature_tensors = {}
      for concat_name, tensor in output_feature_dict.items():
          if (
              get_feature_name_from_concat_name(concat_name)
              == feature_name
          ):
              single_output_feature_tensors[
                  get_tensor_name_from_concat_name(concat_name)
              ] = tensor
      return single_output_feature_tensors
  
file_path: ludwig/ludwig/utils/output_feature_utils.py
imports: from typing import Dict, List
  import numpy
  import torch
  from ludwig.utils.torch_utils import sequence_length_3D, sequence_mask
label_desc: Use image node_id 4 for calling a global function with example usage: get_single_output_feature_tensors(output_feature_dict, feature_name) and returns: single_output_feature_tensors